Results 91 to 100 of about 1,218 (212)
Exoplanet systems are thought to evolve on secular timescales over billions of years. This evolution is impossible to directly observe on human timescales in most individual systems.
Stephen P. Schmidt +2 more
doaj +1 more source
The ubiquity of “peas-in-a-pod” architectural patterns and the existence of the radius valley each presents a striking population-level trend for planets with R _p ≤ 4 R _⊕ that serves to place powerful constraints on the formation and evolution of these
Armaan V. Goyal, Songhu Wang
doaj +1 more source
Differentiation of silicates and iron during formation of Mercury and high-density exoplanets [PDF]
Sergei Nayakshin
openalex +1 more source
Interior heating drives the formation of clouds on exoplanet gas giants [PDF]
Orkun Temel +4 more
openalex +1 more source
The Radius Cliff is a Waterfall: Explaining Sub-Neptune Exoplanets with Steam Worlds
The demographics of Kepler planets provide a key testbed for models of planet formation and evolution, particularly for explaining the radius valley separating super-Earths and sub-Neptunes.
Aritra Chakrabarty +3 more
doaj +1 more source
The Kepler-observed distribution of planet sizes has revealed two distinct patterns: (1) a radius valley separating super-Earths and sub-Neptunes and (2) a preference for intrasystem size similarity.
Matthias Y. He, Eric B. Ford
doaj +1 more source
Characterization of exoplanets from their formation III: The statistics of planetary luminosities [PDF]
C. Mordasini +2 more
openalex +1 more source
Analytical model for starshade formation flying with applications to exoplanet direct imaging observation scheduling [PDF]
Gabriel Soto +2 more
openalex +1 more source
Exoplanet formation inference using conditional invertible neural networks
The interpretation of the origin of observed exoplanets is usually done only qualitatively due to uncertainties of key parameters in planet formation models. To allow a quantitative methodology which traces back in time to the planet birth locations, we train recently developed conditional invertible neural networks (cINN) on synthetic data from a ...
Remo Burn +3 more
openaire +2 more sources

